Automatic Color-to-Gray Conversion for Digital Images in Gradient Domain

Lu Hao, Jie Feng, Bingfeng Zhou

2015

Abstract

Color-to-grayscale conversion for digital color images is widely used in many applications. In this paper an automatic gradient domain color-to-gray conversion method is described. By enhancing the luminance gradient with a modulated chromatic difference enhancement in CIELAB space, a gradient field is created to construct the resulting grayscale image using a Poisson equation solver. A sign function for the gradient is defined for isoluminance color images to keep correct color ordering. By introducing a structural similarity index measurement (SSIM), the main parameters of the method are automatically optimized in the sense of human vision. Therefore, this method can automatically produce artifact-free and salience-preserving grayscale images that coincide with human perception for the color difference.

References

  1. Ancuti, C., Ancuti, C., and Bekaert, P. (2011). Enhancing by saliency-guided decolorization. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 257-264.
  2. Fattal, R., Lischinski, D., and Werman, M. (2002). Gradient domain high dynamic range compression. In SIGGRAPH 7802: Proceedings of the 29th annual conference on Computer graphics and interactive techniques, pages 249-256, New York, NY, USA. ACM.
  3. Gooch, A. A., Olsen, S. C., Tumblin, J., and Gooch, B. (2005). Color2gray: Salience-preserving color removal. In ACM SIGGRAPH 2005 Papers, SIGGRAPH 7805, pages 634-639, New York, NY, USA. ACM.
  4. Grundland, M. and Dodgson, N. A. (2007). Decolorize: Fast, contrast enhancing, color to grayscale conversion. Pattern Recogn., 40(11):2891-2896.
  5. Ishihara, S. (1917). Test for coiour-blindness. Hongo Harukicho.
  6. Kim, Y., Jang, C., Demouth, J., and Lee, S. (2009). Robust color-to-gray via nonlinear global mapping. In SIGGRAPH Asia 7809: ACM SIGGRAPH Asia 2009 papers, pages 1-4, New York, NY, USA. ACM.
  7. Lu, C., Xu, L., and Jia, J. (2012a). Contrast preserving decolorization. In Computational Photography (ICCP), 2012 IEEE International Conference on, pages 1-7. IEEE.
  8. Lu, C., Xu, L., and Jia, J. (2012b). Real-time contrast preserving decolorization. In SIGGRAPH Asia 2012 Technical Briefs, SA 7812, pages 34:1-34:4, New York, NY, USA. ACM.
  9. McCann, J. and Pollard, N. S. (2008). Real-time gradientdomain painting. In SIGGRAPH 7808: ACM SIGGRAPH 2008 papers, pages 1-7, New York, NY, USA. ACM.
  10. Neumann, L., C?adík, M., and Nemcsics, A. (2007). An efficient perception-based adaptive color to gray transformation. In Proceedings of Computational Aesthetics 2007, pages 73- 80, Banff, Canada. Eurographics Association.
  11. Ohta, N. and Robertson (2005). Colorimetry: Fundamentals and Applications. Wiley& Sons, New York.
  12. Pascale, D. (2003). A review of rgb color spaces ... from xyY to R'G'B'. Babel Color.
  13. Pérez, P., Gangnet, M., and Blake, A. (2003). Poisson image editing. In SIGGRAPH 7803: ACM SIGGRAPH 2003 Papers, pages 313-318, New York, NY, USA. ACM.
  14. Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. (1992). Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, New York, NY, USA.
  15. Rasche, K., Geist, R., and Westall, J. (2005). Re-coloring images for gamuts of lower dimension. Computer Graphics Forum, 24(3):423-432.
  16. Shevell, S. K. (2003). The Science of Color. Elsevier, Oxford, UK.
  17. Smith, K., Landes, P.-E., Thollot, J., and Myszkowski, K. (2008). Apparent greyscale: A simple and fast conversion to perceptually accurate images and video. Computer Graphics Forum, 27(2):193-200.
  18. Wang, Z., Bovik, A., Sheikh, H., and Simoncelli, E. (2004). Image quality assessment: From error visibility to structural similarity. Image Processing, IEEE Transactions on, 13(4):600-612.
  19. Wyszecki, G. and Stiles, W. S. (1982). Color Science: Concepts and Methods, Quantitative Data and Formulae. Wiley-Interscience, New York, NY, USA, 2 edition.
  20. Zhou, B. and Feng, J. (2012). Gradient domain saliencepreserving color-to-gray conversion. In SIGGRAPH Asia 2012 Technical Briefs, SA 7812, pages 8:1-8:4, New York, NY, USA. ACM.
Download


Paper Citation


in Harvard Style

Hao L., Feng J. and Zhou B. (2015). Automatic Color-to-Gray Conversion for Digital Images in Gradient Domain . In Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015) ISBN 978-989-758-087-1, pages 231-238. DOI: 10.5220/0005262102310238


in Bibtex Style

@conference{grapp15,
author={Lu Hao and Jie Feng and Bingfeng Zhou},
title={Automatic Color-to-Gray Conversion for Digital Images in Gradient Domain},
booktitle={Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)},
year={2015},
pages={231-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005262102310238},
isbn={978-989-758-087-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)
TI - Automatic Color-to-Gray Conversion for Digital Images in Gradient Domain
SN - 978-989-758-087-1
AU - Hao L.
AU - Feng J.
AU - Zhou B.
PY - 2015
SP - 231
EP - 238
DO - 10.5220/0005262102310238